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The neutral theory is dead. The current significance and standing of neutral and nearly neutral theories
Author(s) -
Ohta Tomoko
Publication year - 1996
Publication title -
bioessays
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.175
H-Index - 184
eISSN - 1521-1878
pISSN - 0265-9247
DOI - 10.1002/bies.950180811
Subject(s) - neutral theory of molecular evolution , nonsynonymous substitution , neutral mutation , neutral network , selection (genetic algorithm) , null hypothesis , substitution (logic) , negative selection , biology , genetic drift , energetic neutral atom , evolutionary biology , positive selection , null model , natural selection , genetics , gene , genetic variation , physics , statistics , mathematics , philosophy , ecology , computer science , ion , quantum mechanics , linguistics , genome , machine learning , artificial intelligence , artificial neural network
Abstract Comparative studies of DNA sequences provide opportunities for testing the neutral and the selection theories of molecular evolution. In particular, the separate estimation of the numbers of synonymous and nonsynonymous substitutions is a powerful tool for detecting selection of the latter. The difference in the patterns of these two types of substitutions of mammalian genes turned out to be in accord with the slightly deleterious or nearly neutral mutation theory for nonsynonymous changes. Interaction systems at the amino acid level were suggested to be responsible for such nearly neutral, or very weak, selection. Synonymous substitutions are not strictly neutral, but because of their minute effect, random drift predominates such that the rate of substitution is only slightly less than the completely neutral prediction. It was concluded that the strictly neutral theory has not held up as well as the nearly neutral theory, yet remains invaluable as a null hypothesis for detecting selection. On the other hand, the main difference between the nearly neutral and the traditional selection theories is that the former predicts rapid evolution in small populations, whereas the latter predicts rapid evolution in large populations.